doi:  10.3878/j.issn.1006-9895.2013.13159
基于卫星资料同化和LAPS-WRF模式系统的云天太阳辐射数值模拟改进方法

Improved Method of Solar Radiation Simulation on Cloudy Days with LAPS-WRF Model System Based on Satellite Data Assimilation
摘要点击 3895  全文点击 2764  投稿时间:2013-04-23  修订日期:2013-11-05
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基金:  国家自然科学基金41275114,国家高技术研究发展计划项目 2011AA05A302
中文关键词:  卫星资料同化  太阳辐射  光伏发电  太阳能  LAPS-WRF模式系统
英文关键词:  Satellite data assimilation  Solar radiation  Photovoltaic power  Solar energy  LAPS-WRF model
                    
作者中文名作者英文名单位
程兴宏CHENG Xinghong中国气象局公共气象服务中心, 北京100081
刘瑞霞LIU Ruixia国家气象卫星中心, 北京100081
申彦波SHEN Yanbo中国气象局公共气象服务中心, 北京100081
朱蓉ZHU Rong国家气候中心, 北京100081
彭继达PENG Jida福建省气象科学研究所, 福州350001
杨振斌YANG Zhenbin中国气象局公共气象服务中心, 北京100081
徐洪雄XU Hongxiong中国气象科学研究院, 北京100081
引用:程兴宏,刘瑞霞,申彦波,朱蓉,彭继达,杨振斌,徐洪雄.2014.基于卫星资料同化和LAPS-WRF模式系统的云天太阳辐射数值模拟改进方法[J].大气科学,38(3):577-589,doi:10.3878/j.issn.1006-9895.2013.13159.
Citation:CHENG Xinghong,LIU Ruixia,SHEN Yanbo,ZHU Rong,PENG Jida,YANG Zhenbin,XU Hongxiong.2014.Improved Method of Solar Radiation Simulation on Cloudy Days with LAPS-WRF Model System Based on Satellite Data Assimilation[J].Chinese Journal of Atmospheric Sciences (in Chinese),38(3):577-589,doi:10.3878/j.issn.1006-9895.2013.13159.
中文摘要:
      太阳能光伏发电已成为仅次于水电和风能的第三大可再生能源,光伏发电受云量时空变化的影响较大,因此准确模拟云天太阳辐射的时空变化对电网安全运行至关重要。围绕如何减小中尺度气象模式的云初始场误差,进而改进云天的太阳辐射模拟这一关键科学问题,本文通过研究基于卫星资料同化的LAPS(Local Analysis Prediction System)多时间层三维云分析同化方法,改进三维云结构,并将LAPS模式输出结果作为WRF(Weather Research and Forecasting)模式的初始场,模拟了2008年1月及夏季(6~8月)北京地区的总云量和总辐射的时空分布,重点分析了多云和有降水天气过程总辐射的模拟改进效果及其原因。结果表明,同化前后的总云量模拟值与观测值的时间变化趋势基本一致,但大部分时次总云量的模拟值低于观测值;大部分多云及降水时段同化后总云量模拟值较接近于实测值。1月晴天、多云天以及夏季晴天同化前后总辐射模拟值与实测值的时间变化趋势较一致,但同化前后两者的相关性差异不明显;晴天条件下同化前后总辐射模拟值均低于实测值,1月多云条件下多数时段同化后总辐射模拟误差减小不明显,与总云量的改进效果不显著有关。夏季多云、有降水及6月典型降水三种天气条件下同化前后总辐射模拟值与观测值的相关性稍差,同化后两者的相关性较同化前有所改进,尤其是6月典型降水过程改进效果较明显;同化前总辐射模拟误差较大,而同化后误差显著减小,尤其是6月典型降水过程同化后均方根误差和平均相对误差较同化前分别减小了102.6 W m-2和355.9%,最大相对误差减小更显著;同化后总辐射模拟误差小于同化前的比例高达75%,即大部分时刻同化后模拟误差小于同化前。多云和有降水天气过程总辐射模拟效果的显著改进与总云量的改进密切相关,即同化后总云量模拟值增加,云的反射和散射作用增强,导致模拟总辐射减小,即更接近于实测总辐射值。研究结果对于多云和降水天气条件下太阳辐射的模拟效果改进、太阳能资源客观评估以及光伏电站的发电量预测具有一定的科学和实际应用价值。
Abstract:
      Photovoltaic power is influenced by the temporal and spatial variation of cloud amounts. Therefore, to ensure safe operation of power grids on cloudy days, accuracy in simulating and forecasting temporal and spatial variations of solar radiation is critical. To reduce initial field errors in the mesoscale meteorological model and to improve the simulation accuracy of solar radiation on cloudy days, the three-dimensional cloud analysis assimilation method in the Local Analysis and Prediction System (LAPS is adopted in this study. The results are used to improve cloud simulation and are used as the initial field of the Weather Research and Forecasting (WRF model. The temporal and spatial distribution characteristics of the total cloud amount and global radiation in the Beijing area in January, June, July, and August and during the typical precipitation processes in June 2008 are simulated with the LAPS-WRF model system. This study focuses on the simulation results of global radiation with and without Fengyun satellite data assimilation and describes the reasons for the improvements on cloudy days and during the precipitation processes. The results showed that the temporal variation of simulated and observed values of total cloud amounts with and without satellite data assimilation were consistent. Without assimilation, the simulated values were significantly lower than observations in most cases. After assimilation, the simulated values of total cloud amounts were closer to observations. In addition, the correlation coefficients between simulation and observation values of global radiation before and after assimilation were higher and the differences of correlation coefficients with and without satellite data assimilation were smaller on clear and cloudy days in January and on clear days in summer. The simulation values of global radiation before and after assimilation were all lower than the measured values on sunny days. After assimilation, the error reduction of global radiation was not noticeable on cloudy days in January because the improvement of total cloud amount simulation was insignificant. Moreover, before and after assimilation, the correlation coefficients between simulation and observation values of global radiation on cloudy and rainy days in summer and during typical precipitation process in June were smaller than those on clear days. However, the correlation coefficients after assimilation were noticeably larger than those before assimilation, particularly during typical precipitation processes in June. Further, simulation errors in global radiation were significantly reduced. For example, the root mean square error and average relative errors during a typical precipitation process in June were reduced by 102.6 W m-2 and 355.9%, respectively, and maximum relative error was reduced to a greater extent. Simulation errors in global radiation after assimilation in most cases were less than those before assimilation, with reduction ratios being 75%. The significant improvement in the simulation of global radiation after assimilation during cloudy days and precipitation processes is closely related to the improvement in total cloud amount. The results of this study have certain scientific and practical application values for the improvement of simulation and the forecasting of solar radiation and photovoltaic power on cloudy days and during precipitation process, and the objective assessments of solar energy resources.
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